Evaluation of Long-Term Pavement Performance (LTPP) Climatic Data for Use in Mechanistic-Empirical Pavement Design Guide (MEPDG) Calibration and Other Pavement Analysis

Chapter 4. MODERN ERA RETROSPECTIVE-ANALYSIS FOR RESEARCH AND APPLICATIONS (MERRA)

The MERRA product from NASA is a new alternative for obtaining high-quality atmospheric and surface weather history data.^(44,45) MERRA is a physics-based reanalysis model that combines computed model fields (e.g., atmospheric temperatures) with ground-, ocean-, atmospheric-, and satellite-based observations that are distributed irregularly in space and time. The result is a uniformly gridded dataset of meteorological data derived from a consistent model and analysis system over the entire data history. MERRA improves on earlier generations of reanalysis models such as those developed by NOAA’s National Center for Environmental Prediction, the European Centre for Medium-Range Weather Forecasts, and the Japan Meteorological Agency.^(46,47,48)

Distribution of MERRA data is funded by NASA’s Science Mission Directorate. The data are not copyrighted and are open to all for both commercial and noncommercial uses. NASA uses MERRA to help verify seasonal climate forecasting systems, generate climate data records, serve as input to satellite retrieval algorithms, and provide atmospheric forcings for hydrologic and land surface process studies.⁽⁴⁹⁾ In addition, MERRA is regularly evaluated and validated to ensure continuity and consistency because the data product is produced in near real-time.

MERRA data are provided at an hourly temporal resolution and a 0.5-degree by 0.67-degree (latitude/longitude) spatial resolution from 1979 to the present. Figure 7 illustrates graphically the spatial density of MERRA grid points over the continental United States; MERRA spans the entire globe at this spatial resolution. For contrast, figure 8 shows the spatial distribution and density (computed as the number of ASOS stations per MERRA grid pixel) of first-order ASOS ground-based weather stations over the continental United States; the ASOS coverage is limited to the United States. The ASOS OWSs are the primary source of climate data for the MEPDG weather database. The higher spatial resolution and larger geographic scope of the MERRA data are clear. In addition, NASA is currently upgrading MERRA to a 0.62- by 0.62-mi horizontal resolution.

The merger of the GEOS-5 model with observations is based on the Grid-Point Statistical Interpolation (GSI), which is a three-dimensional variational data assimilation analysis algorithm. Prior to assimilation, the available observations undergo a sophisticated QC/quality assurance (QA) procedure. Only observations that pass the QC/QA procedure are used during assimilation. For a given 6-h assimilation window, the GEOS-5 model first predicts the background (predictor) states over which the GSI analysis is computed (figure 9). Next, an incremental analysis update (IAU) procedure is conducted during which the analysis correction is applied to the forecast model gradually over the 6-h assimilation window. In essence, the IAU serves to move the model forecast toward closer agreement with the assimilated observations without introducing abrupt discontinuities or physical inconsistencies into the model dynamics. Once the IAU procedure has completed the given 6-h assimilation window, the model advances forward in time to the next 6-h window. This process is repeated over the course of the more than 30-year observation record. More than 4 million observations (mostly satellite-derived) are typically ingested during a 6-h assimilation cycle. For more details on the GEOS-5 model and the GSI procedure, the reader is referred to Rienecker et al.⁽⁴⁴⁾

Figure 7. Map. Map of MERRA grid points over the continental United States where each grid point is approximately 31.1 by 37.3 mi at mid-latitudes.

Figure 8. Map. Spatial distribution and density of first-order ASOS stations over the continental United States.

Source: M.M. Rienecker et al.

Figure 9. Illustration. Schematic of the IAU procedure in MERRA (from Rienecker et al.) shown in Greenwich Mean Time.⁽⁴⁴⁾

MERRA is capable of providing all of the weather history inputs required by the MEPDG and other current infrastructure applications. Table 2 contains the MERRA data elements used to develop MEPDG weather history inputs. In addition, MERRA contains additional data elements useful for enhancements of current infrastructure applications and/or for support of future applications. Samples of available data elements are provided in table 3. A complete listing of all MERRA data elements can be found at http://gmao.gsfc.nasa.gov/products/documents/MERRA_File_Specification.pdf.

Table 2. MERRA data elements available to develop MEPDG weather history inputs.⁽⁴⁵⁾

Table 3. Examples of other MERRA data elements of potential interest for transportation infrastructure applications.⁽⁴⁵⁾

MERRA is freely available to all research agencies and universities through the NASA Modeling and Assimilation Data and Information Services Center (MDISC) at http://disc.sci.gsfc.nasa.gov/daac-bin/DataHoldings.pl. Subsets of the MERRA data at an hourly resolution as a function of time and space can be requested from MDISC, including specification of the desired data element(s). Once the timeframe, region of the globe, and MERRA data elements of interest are selected, the data files are retrieved by NASA in Hierarchical Data Format (HDF) or Network Common Data Form (NetCDF) format. The HDF and NetCDF supercomputer data formats are the only data formats currently supported by NASA to keep storage of the large dataset sizes tractable. Once NASA retrieves the requested data files, they are posted to a public FTP server for access by the user. A number of computing languages (e.g., C++, FORTRAN, IDL, and MATLAB®) contain HDF and NetCDF libraries that can be employed to open the MERRA data files, extract the relevant locations in space and time, and prepare the data for subsequent use in MEPDG or any other infrastructure application of interest.